Synthetic YOLO Dataset Generator
Generate synthetic YOLO datasets for object detection and segmentation—fast, customizable, no coding.
by Wild Cats Dev
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The Synthetic YOLO Dataset Generator is a powerful Unity tool designed to create high-quality synthetic datasets for training computer vision models—specifically object detection and segmentation tasks using the YOLO format.
This package enables you to generate thousands of labeled images directly within the Unity Editor, using fully customizable prefabs and intuitive inspector settings. No coding is required.
🔧 Key Capabilities:
- Generate datasets for YOLO object detection and polygon segmentation
- Add post-processing effects (Depth of Field, Motion Blur, Color Grading, etc.)
- Use randomized lighting, object rotation across custom axes, and random cropping
- Export structured datasets ready for training (train/val/test split)
- Instantly preview labeled results with the included "labeled" folder
⚙️ Customization:
- Supports any Unity 3D object with a renderer
- Fully configurable via the Inspector (camera setup, lighting, resolution, output path, etc.)
- Create and save prefab variants for different use cases (vehicles, characters, tools, etc.)
- Works with YOLOv8-YOLOv12 formats
🎯 Use Cases:
- AI training for autonomous vehicles, robotics, security, and AR
- Game developers prototyping ML-driven gameplay features
- Researchers generating diverse computer vision datasets without manual labeling
Whether you're building a real-time object detector or training a deep learning model, this tool helps you accelerate your data pipeline—right inside Unity.
The instruction is attached to the asset. see Synthetic YOLO Dataset Generator – User Guide.pdf file.
YouTube video instruction:
https://youtu.be/lB1KbAwrBJI
Recommended Unity versions >6000.1.0f1. Earlier versions require Universal Render Pipeline (URP) package installed.
Email for support and feedback:
